Abstract: In the SHP, LVDT sensor is for detecting the length
changes of the EHA output, and the thrust of the EHA is controlled by
the pressure sensor. Sensor is possible to cause hardware fault by
internal problem or external disturbance. The EHA of SHP is able to
be uncontrollable due to control by feedback from uncertain
information, on this paper; the sliding mode observer algorithm
estimates the original sensor output information in permanent sensor
fault. The proposed algorithm shows performance to recovery fault of
disconnection and short circuit basically, also the algorithm detect
various of sensor fault mode.
Abstract: In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.
Abstract: We present a family of data-reusing and affine
projection algorithms. For identification of a noisy linear finite
impulse response channel, a partial knowledge of a channel,
especially noise, can be used to improve the performance of
the adaptive filter. Motivated by this fact, the proposed scheme
incorporates an estimate of a knowledge of noise. A constraint, called
the adaptive noise constraint, estimates an unknown information of
noise. By imposing this constraint on a cost function of data-reusing
and affine projection algorithms, a cost function based on the adaptive
noise constraint and Lagrange multiplier is defined. Minimizing the
new cost function leads to the adaptive noise constrained (ANC)
data-reusing and affine projection algorithms. Experimental results
comparing the proposed schemes to standard data-reusing and affine
projection algorithms clearly indicate their superior performance.
Abstract: Due to the increasing growth of internet users, the emerging applications of multicast are growing day by day and there is a requisite for the design of high-speed switches/routers. Huge amounts of effort have been done into the research area of multicast switch fabric design and algorithms. Different traffic scenarios are the influencing factor which affect the throughput and delay of the switch. The pointer based multicast scheduling algorithms are not performed well under non-uniform traffic conditions. In this work, performance of the switch has been analyzed by applying the advanced multicast scheduling algorithm OQSMS (Optimal Queue Selection Based Multicast Scheduling Algorithm), MDDR (Multicast Due Date Round-Robin Scheduling Algorithm) and MDRR (Multicast Dual Round-Robin Scheduling Algorithm). The results show that OQSMS achieves better switching performance than other algorithms under the uniform, non-uniform and bursty traffic conditions and it estimates optimal queue in each time slot so that it achieves maximum possible throughput.
Abstract: This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.
Abstract: Bezier curves have useful properties for path
generation problem, for instance, it can generate the reference
trajectory for vehicles to satisfy the path constraints. Both algorithms
join cubic Bezier curve segment smoothly to generate the path. Some
of the useful properties of Bezier are curvature. In mathematics,
curvature is the amount by which a geometric object deviates from
being flat, or straight in the case of a line. Another extrinsic example
of curvature is a circle, where the curvature is equal to the reciprocal
of its radius at any point on the circle. The smaller the radius, the
higher the curvature thus the vehicle needs to bend sharply. In this
study, we use Bezier curve to fit highway-like curve. We use
different approach to find the best approximation for the curve so that
it will resembles highway-like curve. We compute curvature value by
analytical differentiation of the Bezier Curve. We will then compute
the maximum speed for driving using the curvature information
obtained. Our research works on some assumptions; first, the Bezier
curve estimates the real shape of the curve which can be verified
visually. Even though, fitting process of Bezier curve does not
interpolate exactly on the curve of interest, we believe that the
estimation of speed are acceptable. We verified our result with the
manual calculation of the curvature from the map.
Abstract: The Com-Poisson (CMP) model is one of the most
popular discrete generalized linear models (GLMS) that handles
both equi-, over- and under-dispersed data. In longitudinal context,
an integer-valued autoregressive (INAR(1)) process that incorporates
covariate specification has been developed to model longitudinal
CMP counts. However, the joint likelihood CMP function is
difficult to specify and thus restricts the likelihood-based estimating
methodology. The joint generalized quasi-likelihood approach
(GQL-I) was instead considered but is rather computationally
intensive and may not even estimate the regression effects due
to a complex and frequently ill-conditioned covariance structure.
This paper proposes a new GQL approach for estimating the
regression parameters (GQL-III) that is based on a single score vector
representation. The performance of GQL-III is compared with GQL-I
and separate marginal GQLs (GQL-II) through some simulation
experiments and is proved to yield equally efficient estimates as
GQL-I and is far more computationally stable.
Abstract: The practical efficient approach is suggested for
estimation of the seismoacoustic sources energy in C-OTDR
monitoring systems. This approach is represents the sequential plan
for confidence estimation both the seismoacoustic sources energy, as
well the absorption coefficient of the soil. The sequential plan
delivers the non-asymptotic guaranteed accuracy of obtained
estimates in the form of non-asymptotic confidence regions with
prescribed sizes. These confidence regions are valid for a finite
sample size when the distributions of the observations are unknown.
Thus, suggested estimates are non-asymptotic and nonparametric,
and also these estimates guarantee the prescribed estimation accuracy
in form of prior prescribed size of confidence regions, and prescribed
confidence coefficient value.
Abstract: A retrospective study conducted at Christian Medical
College (CMC) Teaching Hospital, Vellore, India on 14th August
2014 to assess the accuracy of clinically estimated foetal weight upon
labour admission. Estimating foetal weight is a crucial factor in
assessing maternal and foetal complications during and after labour.
Medical notes of ninety-eight postnatal women who fulfilled the
inclusion criteria were studied to evaluate the correlation between
their recorded Estimated Foetal Weight (EFW) on admission and
actual birth weight (ABW) of the newborn after delivery. Data
concerning maternal and foetal demographics was also noted.
Accuracy was determined by absolute percentage error and
proportion of estimates within 10% of ABW. Actual birth weights
ranged from 950-4080g. A strong positive correlation between EFW
and ABW (r=0.904) was noted. Term deliveries (≥40 weeks) in the
normal weight range (2500-4000g) had a 59.5% estimation accuracy
(n=74) compared to pre-term (4000g) were underestimated by 25% (n=3) and low birthweight
(LBW) babies were overestimated by 12.7% (n=9). Registrars who
estimated foetal weight were accurate in babies within normal weight
ranges. However, there needs to be an improvement in predicting
weight of macrosomic and LBW foetuses. We have suggested the use
of an amended version of the Johnson’s formula for the Indian
population for improvement and a need to re-audit once
implemented.
Abstract: The wider growing Finite Element Method (FEM)
application is caused by its benefits of cost saving and environment
friendly. Also, by using FEM a deep understanding of certain
phenomenon can be achieved. This paper observed the role of
material properties and volumetric change when Solid State Phase
Transformation (SSPT) takes place in residual stress formation due to
a welding process of ferritic steels through coupled Thermo-
Metallurgy-Mechanical (TMM) analysis. The correctness of FEM residual stress prediction was validated by
experiment. From parametric study of the FEM model, it can be
concluded that the material properties change tend to over-predicts
residual stress in the weld center whilst volumetric change tend to
underestimates it. The best final result is the compromise of both by
incorporates them in the model which has a better result compared to
a model without SSPT.
Abstract: Adequate and reliable estimates of aquifer parameters
are of utmost importance for proper management of vital
groundwater resources. At present scenario, the ground water is
polluted because of industrial waste disposed over the land and the
contaminants are transported in the aquifer from one area to another
area, which is depending on the characteristics of the aquifer and
contaminants. To know the contaminant transport, the accurate
estimation of aquifer properties is highly needed. Conventionally,
these properties are estimated through pumping tests carried out on
water wells. The occurrence and movement of ground water in the
aquifer are characteristically defined by the aquifer parameters. The
pumping (aquifer) test is the standard technique for estimating
various hydraulic properties of aquifer systems, viz., transmissivity
(T), hydraulic conductivity (K), storage coefficient (S) etc., for which
the graphical method is widely used. The study area for conducting
pumping test is Pydibheemavaram Industrial area near the coastal
belt of Srikulam, AP, India. The main objective of the present work is
to estimate the aquifer properties for developing contaminant
transport model for the study area.
Abstract: People, throughout the history, have made estimates
and inferences about the future by using their past experiences.
Developing information technologies and the improvements in the
database management systems make it possible to extract useful
information from knowledge in hand for the strategic decisions.
Therefore, different methods have been developed. Data mining by
association rules learning is one of such methods. Apriori algorithm,
one of the well-known association rules learning algorithms, is not
commonly used in spatio-temporal data sets. However, it is possible
to embed time and space features into the data sets and make Apriori
algorithm a suitable data mining technique for learning spatiotemporal
association rules. Lake Van, the largest lake of Turkey, is a
closed basin. This feature causes the volume of the lake to increase or
decrease as a result of change in water amount it holds. In this study,
evaporation, humidity, lake altitude, amount of rainfall and
temperature parameters recorded in Lake Van region throughout the
years are used by the Apriori algorithm and a spatio-temporal data
mining application is developed to identify overflows and newlyformed
soil regions (underflows) occurring in the coastal parts of
Lake Van. Identifying possible reasons of overflows and underflows
may be used to alert the experts to take precautions and make the
necessary investments.
Abstract: This article presents the main results of a numerical
investigation on the uncertainty of dynamic response of structures
with statistically correlated random damping Gamma distributed. A
computational method based on a Linear Statistical Model (LSM) is
implemented to predict second order statistics for the response of a
typical industrial building structure. The significance of random
damping with correlated parameters and its implications on the
sensitivity of structural peak response in the neighborhood of a
resonant frequency are discussed in light of considerable ranges of
damping uncertainties and correlation coefficients. The results are
compared to those generated using Monte Carlo simulation
techniques. The numerical results obtained show the importance of
damping uncertainty and statistical correlation of damping
coefficients when obtaining accurate probabilistic estimates of
dynamic response of structures. Furthermore, the effectiveness of the
LSM model to efficiently predict uncertainty propagation for
structural dynamic problems with correlated damping parameters is
demonstrated.
Abstract: This paper discusses micrometeorological aspects of the urban climate in three cities in Western São Paulo State: Presidente Prudente, Assis and Iepê. Particular attention is paid to the method used to estimate the components of the energy balance at the surface. Estimates of convective fluxes showed that the Bowen ratio was an indicator of the local climate and that its magnitude varied between 0.3 and 0.7. Maximum values for the Bowen ratio occurred earlier in Iepê (11:00 am) than in Presidente Prudente (4:00 pm). The results indicate that the Bowen ratio is modulated by the radiation balance at the surface and by different clusters of vegetation.
Abstract: The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data of the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as «signaling parameters» (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of COTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources, but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as rule. This report contains describing of the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.
Abstract: Determination of genetic variation is useful for plant
breeding and hence production of more efficient plant species under
different conditions, like drought stress. In this study a sample of 28
recombinant inbred lines (RILs) of wheat developed from the cross of
Norstar and Zagross varieties, together with their parents, were
evaluated for two years (2010-2012) under normal and water stress
conditions using split plot design with three replications. Main plots
included two irrigation treatments of 70 and 140 mm evaporation
from Class A pan and sub-plots consisted of 30 genotypes. The effect
of genotypes and interaction of genotypes with years and water
regimes were significant for all characters. Significant genotypic
effect implies the existence of genetic variation among the lines
under study. Heritability estimates were high for 1000 grain weight
(0.87). Biomass and grain yield showed the lowest heritability values
(0.42 and 0.50, respectively). Highest genotypic and phenotypic
coefficients of variation (GCV and PCV) belonged to harvest index.
Moderate genetic advance for most of the traits suggested the
feasibility of selection among the RILs under investigation. Some
RILs were higher yielding than either parent at both environments.
Abstract: In this paper, an analytical simplified method for
calculating elasto-plastic stresses strains of notched bodies subject to
non-proportional loading paths is discussed. The method was based
on the Neuber notch correction, which relates the incremental elastic
and elastic-plastic strain energy densities at the notch root and the
material constitutive relationship. The validity of the method was
presented by comparing computed results of the proposed model
against finite element numerical data of notched shaft. The
comparison showed that the model estimated notch-root elasto-plastic
stresses strains with good accuracy using linear-elastic stresses. The
prosed model provides more efficient and simple analysis method
preferable to expensive experimental component tests and more
complex and time consuming incremental non-linear FE analysis.
The model is particularly suitable to perform fatigue life and fatigue
damage estimates of notched components subjected to nonproportional
loading paths.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: The development of allometric models is crucial to
accurate forest biomass/carbon stock assessment. The aim of this
study was to develop a set of biomass prediction models that will
enable the determination of total tree aboveground biomass for
savannah woodland area in Niger State, Nigeria. Based on the data
collected through biometric measurements of 1816 trees and
destructive sampling of 36 trees, five species specific and one site
specific models were developed. The sample size was distributed
equally between the five most dominant species in the study site
(Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa,
Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the
equations were developed for five individual species. Secondly these
five species were mixed and were used to develop an allometric
equation of mixed species. Overall, there was a strong positive
relationship between total tree biomass and the stem diameter. The
coefficient of determination (R2 values) ranging from 0.93 to 0.99 P
< 0.001 were realised for the models; with considerable low standard
error of the estimates (SEE) which confirms that the total tree above
ground biomass has a significant relationship with the dbh. F-test
values for the biomass prediction models were also significant at p
Abstract: Emissions of atmospheric pollutants from ships and
harbour activities are a growing concern at international level given
their potential impacts on air quality and climate. These close-to-land
emissions have potential impact on local communities in terms of air
quality and health. Recent studies show that the impact of maritime
traffic to atmospheric particulate matter concentrations in several
coastal urban areas is comparable with the impact of road traffic of a
medium size town. However, several different approaches have been
used for these estimates making difficult a direct comparison of
results. In this work, an integrated approach based on emission
inventories and dedicated measurement campaigns has been applied
to give a comparable estimate of the impact of maritime traffic to
PM2.5 and particle number concentrations in three major harbours of
the Adriatic/Ionian Seas. The influences of local meteorology and of
the logistic layout of the harbours are discussed.